Package: SGCP 1.12.0

Niloofar AghaieAbiane

SGCP: SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks

SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.

Authors:Niloofar AghaieAbiane [aut, cre], Ioannis Koutis [aut]

SGCP_1.12.0.tar.gz
SGCP_1.12.0.zip(r-4.7)SGCP_1.12.0.zip(r-4.6)SGCP_1.12.0.zip(r-4.5)
SGCP_1.12.0.tgz(r-4.6-any)SGCP_1.12.0.tgz(r-4.5-any)
SGCP_1.12.0.tar.gz(r-4.7-any)SGCP_1.12.0.tar.gz(r-4.6-any)
SGCP_1.12.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SGCP/json (API)
NEWS

# Install 'SGCP' in R:
install.packages('SGCP', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/na396/sgcp/issues

Datasets:
  • cheng - Normalized gene expression data from Cheng et al.'s publication on ischemic cardiomyopathy (ICM).
  • resClus - An example of the output from 'clustering' function in the SGCP pipeline
  • resFinalGO - An example of the output from 'geneOntololgy' function in the SGCP pipeline
  • resInitialGO - An example of the output from the 'geneOntololgy' function in the SGCP pipeline
  • resSemiLabel - An example of the output from 'semiLabeling' function in the SGCP pipeline
  • resSemiSupervised - An example of the output from 'semiSupervised' function in the SGCP pipeline
  • sgcp - An example of the output of 'ezSGCP' function in the SGCP pipeline

On CRAN:

Conda:

geneexpressiongenesetenrichmentnetworkenrichmentsystemsbiologyclassificationclusteringdimensionreductiongraphandnetworkneuralnetworknetworkmrnamicroarrayrnaseqvisualizationbioinformaticsgenecoexpressionnetworkgraphsnetworkclusteringnetworksself-trainingsemi-supervised-learningunsupervised-learning

3.14 score 2 stars 46 scripts 206 downloads 15 exports 149 dependencies

Last updated from:7323764cf5 (on RELEASE_3_23). Checks:8 WARNING, 1 ERROR, 1 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksWARNING268
linux-devel-x86_64WARNING528
source / vignettesERROR419
linux-release-x86_64WARNING537
macos-release-arm64WARNING296
macos-oldrel-arm64WARNING310
windows-develWARNING325
windows-releaseWARNING403
windows-oldrelWARNING343
wasm-releaseOK225

Exports:adjacencyMatrixclusteringezSGCPgeneOntologysemiLabelingsemiSupervisedSGCP_ezPLOTSGCP_plot_barSGCP_plot_conductanceSGCP_plot_densitySGCP_plot_heatMapSGCP_plot_jitterSGCP_plot_pcaSGCP_plot_pieSGCP_plot_silhouette

Dependencies:abindannotateAnnotationDbiAnnotationForgeaskpassBHBiobaseBiocGenericsBiostringsbitbit64bitopsblobbootcachemcaretCategorycellrangerclassclicliprclockcodetoolscpp11crayoncurldata.tableDBIDelayedArrayDescToolsdiagramdigestdplyre1071Exactexpmfarverfastmapforcatsforeachfsfuturefuture.applygenefiltergenericsGenomicRangesggplot2ggridgesgldglobalsglueGO.dbGOstatsgowergraphGSEABasegtablehardhathavenhmshttripredIRangesisobanditeratorsjsonliteKEGGRESTKernSmoothlabelinglatticelavalifecyclelistenvlmomlubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeModelMetricsmvtnormnlmennetnumDerivopensslopenxlsxorg.Hs.eg.dbparallellypillarpkgconfigplyrpngprettyunitspROCprodlimprogressprogressrproxypurrrR6RBGLRColorBrewerRcppRcppEigenRCurlreadrreadxlrecipesrematchreshape2RgraphvizrlangrootSolverpartRSpectraRSQLiterstudioapiS4ArraysS4VectorsS7scalesSeqinfoshapeSparseArraysparsevctrsSQUAREMstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitevroomwithrXMLxtableXVectorzip

Readme and manuals

Help Manual

Help pageTopics
Performs netwrok construction step in the SGCP pipelineadjacencyMatrix
Normalized gene expression data from Cheng et al.'s publication on ischemic cardiomyopathy (ICM).cheng
Perform network clustering step in the SGCP pipelineclustering
Integrated execution of the SGCP pipelineezSGCP
Performs gene ontology enrichment step in the SGCP pipeline.geneOntology
An example of the output from 'clustering' function in the SGCP pipelineresClus
An example of the output from 'geneOntololgy' function in the SGCP pipelineresFinalGO
An example of the output from the 'geneOntololgy' function in the SGCP pipelineresInitialGO
An example of the output from 'semiLabeling' function in the SGCP pipelineresSemiLabel
An example of the output from 'semiSupervised' function in the SGCP pipelineresSemiSupervised
Performs gene semi-labeling step in the SGCP pipelinesemiLabeling
Performs the semi-supervised step in the SGCP pipelinesemiSupervised
An example of the output of 'ezSGCP' function in the SGCP pipelinesgcp
Comprehensive SGCP plotting in one executionSGCP_ezPLOT
Mean p-value bar chart for gene ontology enrichment in the SGCP pipelineSGCP_plot_bar
Cluster conductance index bar chart in the SGCP PipelineSGCP_plot_conductance
Visualization of gene ontology term p-value distribution in the SGCP pipelineSGCP_plot_density
Adjacency matrix heatmap in the SGCP pipelineSGCP_plot_heatMap
P-value jitter chart for gene ontology enrichment in the SGCP pipeline.SGCP_plot_jitter
PCA visualization in the SGCP PipelineSGCP_plot_pca
Gene ontology analysis pie chart in the SGCP pipelineSGCP_plot_pie
Cluster silhouette index chart in the SGCP PipelineSGCP_plot_silhouette